Abstract In this paper we present our experience in the development of a web‐based business intelligence tool according to the Associative Query Logic paradigm, which can represent large amounts of data in a way that allows extremely fast queries. It has been developed as an open‐source, multi‐platform software, relying on data compression techniques for the storage of large amounts of data in the main memory. The performance of our solution in terms of compression, load time and response time is close to that of the commercial tool of reference, QlikView. Moreover, we provide solutions to some open problems in QlikView published description, which may be beneficial to assist in the development of other open or proprietary tools. Copyright © 2010 John Wiley & Sons, Ltd.

This paper focuses on automated content update for MHP applications. Some of the authors have been involved in the first MHP trials of TVG, the TV channel of Galicia, NW Spain (three million population). It has a 30% share at regional level, competing with national channels. However, the initial MHP trials have raised the problem of manual content update cost, since in many key applications, like news and weather forecasts, contents vary on a daily basis. We have reviewed the status of MHP deployment in similar TV channels, and we have determined that the problem is currently relevant. We describe our solutions for automated content update with minimal human intervention, and our practical experience with them.

Abstract For a long time, the design of relational databases has focused on the optimization of atomic transactions (insert, select, update or delete). Currently, relational databases store tactical information of data warehouses, mainly for select‐like operations. However, the database paradigm has evolved, and nowadays on‐line analytical processing (OLAP) systems handle strategic information for further analysis. These systems enable fast, interactive and consistent information analysis of data warehouses, including shared calculations and allocations. OLAP and data warehouses jointly allow multidimensional data views, turning raw data into knowledge. OLAP allows ‘slice and dice’ navigation and a top‐down perspective of data hierarchies. In this paper, we describe our experience in the migration from a large relational database management system to an OLAP system on top of a relational layer (the data warehouse), and the resulting contributions in open‐source ROLAP optimization. Existing open‐source ROLAP technologies rely on summarized tables with materialized aggregate views to improve system performance (in terms of response time). The design and maintenance of those tables are cumbersome. Instead, we intensively exploit cache memory, where key data reside, yielding low response times. A cold start process brings summarized data from the relational database to cache memory, subsequently reducing the response time. We ensure concurrent access to the summarized data, as well as consistency when the relational database updates data. We also improve the OLAP functionality, by providing new features for automating the creation of calculated members. This makes it possible to define new measures on the fly using virtual dimensions, without re‐designing the multidimensional cube. We have chosen the XML/Ade factostandard for service provision. Copyright © 2008 John Wiley & Sons, Ltd.

The parallel hierarchical matching (PHM) algorithm is a distributed maximal size matching scheduler for virtual output-queued switches. In a previous letter, we formulated an upper bound on the maximum number of iterations PHM requires to achieve a maximal size matching in any traffic scenario. In this letter, we follow an analytical approach to find the average number of iterations for PHM to achieve a maximal size matching under diverse traffic models. The estimated number of iterations is O(log2N), as in the case of iSLIP-like algorithms

Diverse social applications rely on remote location of personal devices: house arrest tracker systems, remote monitoring of alcoholic persons, child locator devices and remote protection of victims of domestic abuse are some examples. However, existing personal location devices either depend on a fixed station (a domestic gateway) -thus limiting user mobility-, or include a full cell phone -thus increasing weight, cost and power consumption-. In this demonstration, we present a new system we have developed for the Galician regional government (Spain) to track domestic abusers and their victims. It consists of two units, namely a personal low-cost light microdevice (bracelet in the sequel) and a commercial cell phone. The latter acts as a mobile gateway, which the bracelet accesses via a PAN. By doing so, we benefit from the advantages of the two previous approaches: the small size of bracelets for fixed gateways and the full mobility of those including a full cell phone. Wide-area location capability may reside either in the bracelet (as a GPS modem) or in the mobile gateway (either as a GPS modem or via core network-assisted location). If the bracelet leaves mobile gateway PAN range, the latter alerts the user and/or sends an alarm to a remote monitoring station.

iSLIP and parallel hierarchical matching (PHM) are distributed maximal size matching schedulers for input-buffered switches. Previous research has analyzed the hardware cost of those schedulers and their performance after a small number of iterations. In this paper, we formulate an upper bound for the number of iterations required by PHM to converge. Then, we compare the number of iterations required by iSLIP and PHM to achieve a maximal throughput under uniform Bernoulli traffic, by means of simulation. Finally, we obtain the corresponding delay performances, which are similar. The results suggest that PHM has both the advantages of previous hierarchical matching algorithms (low hardware complexity) and iSLIP (low number of iterations).

Virtual machines for remote execution are a useful tool for utilizing light user interfaces and intensive application cores in different physical machines connected through the Internet. In a virtual machine, application cores are distributed in a network. Specific locations, operating systems and hardware characteristics are hidden by virtual machines. They make it possible to use a PC to execute user interfaces and (a few) high-performance computers for application cores. We present a Java/CORBA-based brokerage platform that allows remote execution of optimization solvers from a client running on any platform. The system offers a dynamic library of available problem solvers, and a graphic interface to browse several defined properties and metadata on available solvers. In addition, an embedded file compression module to reduce data transfer time is included as a plug-in feature of the proposed virtual machine. Analogous systems could be constructed for applications in which interaction traffic time is much lower than execution time. Copyright © 2001 John Wiley & Sons, Ltd.

This paper formulates an incomplete projection algorithm that is applied to the image recovery problem. The algorithm allows an easy implementation of dynamic load balancing for parallel architectures. Furthermore, the local computation-communication load ratio can be adjusted, since each processor performs a finite number of iterations of any projection-type technique, and this number can be provided as a parameter of the algorithm. Numerical results compare favorably with those obtained by the extrapolated method of parallel subgradient projections.